13 citations · 21 across the 4 of their papers we have counts for
5 papers
Patch-wise Features for Blur Image Classification
Sri Charan Kattamuru, Kshitij Agrawal, Shyam Prasad Adhikari +2
Images captured through smartphone cameras often suffer from degradation, blur being one of the major ones, posing a challenge in processing these images for downstream tasks. In t…
Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection
Anay Majee, Anbumani Subramanian, Kshitij Agrawal
Localization and recognition of less-occurring road objects have been a challenge in autonomous driving applications due to the scarcity of data samples. Few-Shot Object Detection…
Few-Shot Batch Incremental Road Object Detection via Detector Fusion
Anuj Tambwekar, Kshitij Agrawal, Anay Majee +1
Incremental few-shot learning has emerged as a new and challenging area in deep learning, whose objective is to train deep learning models using very few samples of new class data,…
Few-Shot Learning for Road Object Detection
Anay Majee, Kshitij Agrawal, Anbumani Subramanian
Few-shot learning is a problem of high interest in the evolution of deep learning. In this work, we consider the problem of few-shot object detection (FSOD) in a real-world, class-…
Enhancing Object Detection in Adverse Conditions using Thermal Imaging
Kshitij Agrawal, Anbumani Subramanian
Autonomous driving relies on deriving understanding of objects and scenes through images. These images are often captured by sensors in the visible spectrum. For improved detection…